Project results provide evidence that compound-specific isotope ratio analysis of hair has the potential to go beyond information on region-of-origin or geospatial movements of individuals to include the identification of physical and characteristic traits of individuals, such as age and body mass index. By quantifying the amount of amino acids in human hair, researchers were able to perform statistical comparisons between donors with different characteristic traits, including sex, age, and region of origin. Using "leave-one-individual-out cross-validation" on more than 80 hair donors, the fuzzy rule-building expert system (FuRES) classification rate was 94 percent for sex, 83 percent for age group, and 61 percent for the region of origin. In addition, researchers used the amino acid profiles of scalp hair of 27 Jordanian subjects to predict diabetes from hair analysis. With FuRES, they were able to classify the amino acid profiles into diabetic and control groups with 100 percent sensitivity and specificity, using leave-one-individual-out cross-validation. The project contributed 100 data points to the publication of a new global database of bulk carbon and nitrogen isotope ratios in human hair containing more than 3,500 analysis results. This can be used by future investigators to provide statistical basis for inclusion or exclusion of evidence. In separate work, researchers used LC-TRMS to measure the isotope ratios of 14 amino acids in hair proteins independently, and leucine/isoleucine as a co-eluting pair to provide 15 variables for classification. Multivariate analysis confirmed that the essential amino acids and non-essential amino acids were mostly independent variables in the classification rules. 15 tables, 15 figures, 75 references, and a listing of sources for dissemination of research findings
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